Many users may utilize search engines to perform search tasks on a regular basis to attempt to address information needs. For example, a user may provide one or more queries to a search engine in an attempt to purchase a pair of cold weather work boots (e.g., “work boot reviews,” “steal toe boots,” “work boot sales,” “warmest boots,” and/or other queries). In order to assist users with such search tasks, search engines may attempt to address information needs of the users, such as by providing users with query recommendations, etc. For example, search logs containing queries previously provided by the user may be evaluated to identify a search session and a search task associated with the search session (e.g., a session-task approach for providing query recommendations). Unfortunately, the session-task approach to satisfying information needs may have limited accuracy because of the nature and/or complexity of how users perform search tasks. For example, search users may engaged in complex and exploratory search tasks that often result in tangential search tasks being initiated (e.g., multi-tasking search behavior, such as a user providing a first set of queries associated with a first search task of researching new cars and a second set of queries associated with a second search task for purchasing cold weather work boots in a single search session). Thus, queries directed to secondary search tasks may be utilized in an attempt to satisfy the information need of users, which may create ambiguity when used to identify the initial search task. As a result of queries being incorrectly associated with a search task, users may be provided with irrelevant query recommendations and/or need to submit multiple search queries to locate desired content. Unfortunately, many computing devices and/or search engines may lack technology that can accurately classify queries submitted by users to address information needs.